Merge branch 'dev' into feat/wandb-logging

configs/example.json

@@ -0,0 +1,8 @@
+{
+  "morphology": {
+    "num_arms": 2,
+    "num_segments_per_arm": 4,
+    "use_p_control": true,
+    "use_torque_control": false
+  }
+}

configs/hpc/smoke_test.yaml

@@ -0,0 +1,11 @@
+# Minimal config to verify HPC setup is functional.
+# Run with: python scripts/train.py --config-path configs/hpc/smoke_test.yaml
+exp_name: "hpc_smoke_test"
+seed: 0
+track: false           # Test WandB integration
+capture_video: false  # No rendering for smoke test
+save_model: true      # Test the end-of-training save routine
+num_envs: 512
+total_timesteps: 65536
+num_steps: 128
+cuda: true

configs/production_training.yaml

@@ -4,34 +4,33 @@
 # with wandb logging enabled.
 
 # Experiment settings
-exp_name: "brittle_star_production"
+exp_name: "brittle_star_production_training"
 seed: 42
 
-# Tracking settings - IMPORTANT: Set your own wandb_entity!
+# Tracking
 track: true
+capture_video: false
 wandb_project_name: "PPO-Modularity"
-wandb_entity: "SEL3-2026-Groep-4"  # ⚠️  SET THIS TO YOUR WANDB USERNAME OR TEAM
+wandb_entity: "SEL3-2026-Groep-4"
 
 # Model saving
 save_model: true
 checkpoint_frequency: 100  # Save checkpoint every 100 iterations
 
 # Environment settings
-num_envs: 32  # Increased for production
+num_envs: 512
 
-# Training hyperparameters - Production scale
-total_timesteps: 50000000  # 50M timesteps for full training
-learning_rate: 0.00025
-num_steps: 256  # Longer rollouts
+# Training hyperparameters
+total_timesteps: 50000000
+num_steps: 256
+num_minibatches: 4
+update_epochs: 4
+
+learning_rate: 2.5e-4
 anneal_lr: true
-
-# PPO specific - Fine-tuned
 gamma: 0.99
 gae_lambda: 0.95
-num_minibatches: 8  # More minibatches for stability
-update_epochs: 4
-norm_adv: true
-clip_coef: 0.2
+clip_coef: 0.1
 clip_vloss: true
 ent_coef: 0.01
 vf_coef: 0.5